knitr::opts_chunk$set(fig.width = 12, 
                      fig.height = 8,
                      fig.align = "center")
library(knitr)

data <- params$data
report.items <- params$report.items

```{css, echo=FALSE} .myheader .property { width:35%; display:inline-block; box-sizing:border-box; text-align:left; vertical-align: top; }

.myheader .value { text-align:left; width:64%; display:inline-block; box-sizing:border-box; }

***

<div class="myheader">
<div class="property">**Sample ID**</div><div class="value">`r data$vcf.file.basename`</div><br>
<div class="property">**Sample VCF File**</div><div class="value">`r paste0(data$vcf.file.basename, ".vcf")`</div><br>
<div class="property">**Sample VCF Genome**</div><div class="value">`r data$vcf.obj$genome`</div><br>
<div class="property">**Sample VCF Total Point Mutations**</div><div class="value">`r format(x = nrow(data$vcf.obj$data), big.mark = ",")`</div><br>
<div class="property">**FIREVAT Execution Start Datetime**</div><div class="value">`r data$start.datetime`</div><br>
<div class="property">**FIREVAT Execution End Datetime**</div><div class="value">`r data$end.datetime`</div><br>
</div>

```r
kable(report.items$df.genetic.algo.params, align = c('l','l'))

1. Refinement Optimization

kable(report.items$df.filter.cutoffs, align = c('l','c','c'))
kable(report.items$df.optimization.results, align = c('l','c','c','c','c'))
print(report.items$refined.muts.optimization.iter.plot)
print(report.items$artifactual.muts.optimization.iter.plot)

2. Optimzed Mutational Signature Identification


2.1. Identified Signatures

print(report.items$identified.signatures.plot)


2.2. Trinucleotide Spectrums

kable(report.items$df.trinucleotide.spectrums, align = c('l','c','c','c'))

2.2.1. Observed Spectrum

print(report.items$observed.spectrums.plot)

2.2.2. Maximum-likelihood Estimation (MLE) Reconstructed Spectrum

print(report.items$mle.reconstructed.spectrums.plot)

2.2.3. Residual Spectrum

print(report.items$residual.spectrums.plot)


2.3. Nucleotide Substitution Types

print(report.items$nucleotide.substitution.types.plot)

3. Optimized VCF Statistics

r height <- (4 * report.items$vcf.stats.plot$params.count)

print(report.items$vcf.stats.plot$fig)

4. Variants with Strand Bias


4.1. Refined VCF

if (is.null(report.items$df.refined.vcf.strand.bias)) {
    cat("None to display.")
}
if (data$annotate) {
    if (nrow(report.items$df.refined.vcf.strand.bias) == 0) {
        cat("None to display.")
    }
    else {
        kable(report.items$df.refined.vcf.strand.bias, 
              align = c('l','r','c','c','c','c','c','c','c'), 
              row.names = FALSE)
    }
}    


4.2. Artifactual VCF

if (is.null(report.items$df.artifact.vcf.strand.bias)) {
    cat("None to display.")
}
if (data$annotate) {
    if (nrow(report.items$df.artifact.vcf.strand.bias) == 0) {
        cat("None to display.")
    }
    else {
        kable(report.items$df.artifact.vcf.strand.bias,
              align = c('l','r','c','c','c','c','c','c','c'),
              row.names = FALSE)
    }
}

5. VCF Annotation (ClinVar)


5.1. Refined VCF

if (is.null(report.items$df.refined.vcf.annotated)) {
    cat("None to display.")
}
if (data$annotate) {
    if (nrow(report.items$df.refined.vcf.annotated) == 0) {
        cat("None to display.")
    }
    else {
        align.vec <- rep("c", ncol(report.items$df.refined.vcf.annotated))
        align.vec[1] <- "l"
        align.vec[2] <- "r"
        kable(report.items$df.refined.vcf.annotated, align = align.vec)
    }
}    


5.2. Artifactual VCF

if (is.null(report.items$df.artifact.vcf.annotated)) {
    cat("None to display.")
}
if (data$annotate) {
    if (nrow(report.items$df.artifact.vcf.annotated) == 0) {
        cat("None to display.")
    }
    else {
        align.vec <- rep("c", ncol(report.items$df.artifact.vcf.annotated))
        align.vec[1] <- "l"
        align.vec[2] <- "r"
        kable(report.items$df.artifact.vcf.annotated, align = align.vec)
    }
}




cgab-ncc/FIREVAT documentation built on Nov. 19, 2022, 5:55 p.m.